all tools / ml
As of the latest check, Glimind tracks 200 ml AI agent (MCP) tools, of which 0 are healthy right now. The table below ranks them live-first by real-time reliability.
| tool | status | what it does | |
|---|---|---|---|
| phaedo_consult io.github.galavoxx/phaedo-mcp | unknown | Consult the decision pattern for a given action; returns a consultation signal (never layer content). | alternatives |
| agents_list Dooor-AI/dooor-os-mcp | unknown | List all agents in the workspace. | alternatives |
| agents_get Dooor-AI/dooor-os-mcp | unknown | Get details of a specific agent by ID. | alternatives |
| set_metric_names optuna-mcp | unknown | Set metric_names. Metric_names are labels used to distinguish what each objective value is. | alternatives |
| create_study optuna-mcp | unknown | Create a new Optuna study with the given study_name and directions. If the study already exists, it will be simply loaded. | alternatives |
| set_sampler optuna-mcp | unknown | Set the sampler for the study. | alternatives |
| get_metric_names optuna-mcp | unknown | Get metric_names. | alternatives |
| get_directions optuna-mcp | unknown | Get the directions of the study. | alternatives |
| get_trials optuna-mcp | unknown | Get all trials in a CSV format. | alternatives |
| best_trial optuna-mcp | unknown | Get the best trial. | alternatives |
| best_trials optuna-mcp | unknown | Return trials located at the Pareto front in the study. | alternatives |
| ask optuna-mcp | unknown | Suggest new parameters using Optuna. | alternatives |
| ai_environment SurathDurgaprasad/MachineProfile MCP | unknown | Details about GPU hardware, local packages (torch, onnxruntime), local Ollama model files, and passive accelerator evidence. | alternatives |
| train_anomaly_model LGDiMaggio/predictive-maintenance-mcp | unknown | Train novelty detection on healthy baselines | alternatives |
| predict_anomalies LGDiMaggio/predictive-maintenance-mcp | unknown | Score a signal against a trained model (bounded output) | alternatives |
| extract_features_from_signal LGDiMaggio/predictive-maintenance-mcp | unknown | Segmented statistical feature extraction | alternatives |
| compute_power_spectral_density LGDiMaggio/predictive-maintenance-mcp | unknown | Power spectral density (Welch method) | alternatives |
| compute_spectrogram_stft LGDiMaggio/predictive-maintenance-mcp | unknown | Time-frequency spectrogram | alternatives |
| check_bearing_faults LGDiMaggio/predictive-maintenance-mcp | unknown | Unified fault-frequency matching (catalog bearing, explicit frequencies, or explicit geometry) | alternatives |
| diagnose_vibration LGDiMaggio/predictive-maintenance-mcp | unknown | Integrated evidence-based diagnosis pipeline (one call) | alternatives |
| calculate_bearing_characteristic_frequencies LGDiMaggio/predictive-maintenance-mcp | unknown | Expected fault frequencies from bearing geometry | alternatives |
| assess_severity LGDiMaggio/predictive-maintenance-mcp | unknown | Unified ISO 20816-3 severity assessment (signal or direct RMS reading, custom thresholds) — requires a declared signal unit, never guesses | alternatives |
| get_ai_performance io.github.genudo-ai/genudo_mcp | unknown | Get AI performance and cost | alternatives |
| analyze_melody FernandoDaSilva-T/music21-mcp | unknown | Contorno, âmbito, intervalos, clímax, lista de notas | alternatives |
| check_pricing runapi-ai/@runapi.ai/runway-aleph-mcp | unknown | Look up current pricing for a Runway Aleph model and endpoint. | alternatives |
| classify_test_failure triagekit-mcp-flaky-test-detective | unknown | Classifies a test's recent history as consistently-failing / consistently-passing / intermittent (flaky) / insufficient-data, with run-by-ru | alternatives |
| ocr_recognize wk-ocr-mcp | unknown | 图片文字识别 - 从任意包含文字的图片中提取文本内容 | alternatives |
| analyze_game io.github.seang1121/sports-betting-mcp | unknown | Full 12-agent analysis on any game: consensus pick + edge breakdown | alternatives |
| slop_detect ahmedak/defluff | unknown | Analyze text for filler phrases and return slop score, spans, categories, and lexicon version. | alternatives |
| propose_campaign_state cscokus/lm-mcp-server | unknown | Propose a campaign state change (writes to AI_Action_Queue). | alternatives |
| propose_new_campaign cscokus/lm-mcp-server | unknown | Propose a new campaign (writes to AI_Action_Queue). | alternatives |
| run_ad_review cscokus/lm-mcp-server | unknown | Run an ad review. | alternatives |
| propose_bid_change cscokus/lm-mcp-server | unknown | Propose a bid change (writes to AI_Action_Queue). | alternatives |
| propose_budget_shift cscokus/lm-mcp-server | unknown | Propose a budget shift (writes to AI_Action_Queue). | alternatives |
| propose_audience_rebuild cscokus/lm-mcp-server | unknown | Propose an audience rebuild (writes to AI_Action_Queue). | alternatives |
| recall_at_k io.github.MukundaKatta/ragmetric-mcp | unknown | Fraction of relevant items in top k | alternatives |
| hit_at_k io.github.MukundaKatta/ragmetric-mcp | unknown | 1.0 if any relevant in top k else 0 | alternatives |
| mrr io.github.MukundaKatta/ragmetric-mcp | unknown | 1 / rank of first relevant, 0 if none | alternatives |
| ndcg_at_k io.github.MukundaKatta/ragmetric-mcp | unknown | NDCG@k with binary relevance (log2 discount) | alternatives |
| evaluate_batch io.github.MukundaKatta/ragmetric-mcp | unknown | Mean of each metric across many queries | alternatives |
| f1_predict_pit_strategy io.github.Ninjabeam20/sportiq-mcp | unknown | Tyre-degradation model on OpenF1 telemetry → optimal stop laps + compound sequence. | alternatives |
| football_find_value_bets io.github.Ninjabeam20/sportiq-mcp | unknown | Find value betting opportunities. | alternatives |
| football_build_accumulator io.github.Ninjabeam20/sportiq-mcp | unknown | Build an accumulator bet. | alternatives |
| f1_tyre_degradation io.github.Ninjabeam20/sportiq-mcp | unknown | Analyze tyre degradation. | alternatives |
| f1_undercut_window io.github.Ninjabeam20/sportiq-mcp | unknown | Analyze undercut window. | alternatives |
| f1_weather_strategy_impact io.github.Ninjabeam20/sportiq-mcp | unknown | Analyze weather impact on strategy. | alternatives |
| f1_qualifying_analysis io.github.Ninjabeam20/sportiq-mcp | unknown | Analyze qualifying performance. | alternatives |
| f1_race_pace_compare io.github.Ninjabeam20/sportiq-mcp | unknown | Compare race pace between drivers. | alternatives |
| football_simulate_bracket io.github.Ninjabeam20/sportiq-mcp | unknown | Monte Carlo with Poisson xG over the 48-team WC 2026 format → per-team round + title probabilities. | alternatives |
| football_xg_model io.github.Ninjabeam20/sportiq-mcp | unknown | Expected goals model for match analysis. | alternatives |
| cricket_captain_recommendation io.github.Ninjabeam20/sportiq-mcp | unknown | Recommend captain for Dream11. | alternatives |
| football_match_predictor io.github.Ninjabeam20/sportiq-mcp | unknown | Predict match outcome based on team data. | alternatives |
| football_simulate_group io.github.Ninjabeam20/sportiq-mcp | unknown | Simulate group stage outcomes. | alternatives |
| football_knockout_path io.github.Ninjabeam20/sportiq-mcp | unknown | Determine knockout path for a team. | alternatives |
| cricket_build_dream11_team io.github.Ninjabeam20/sportiq-mcp | unknown | PuLP constraint solver → a valid fantasy XI under credit/role/team caps. | alternatives |
| classify_ai_system services.gera/mcp-gera-compliance | unknown | Run the EU AI Act risk classification from boolean answer keys. Returns the risk tier, triggered articles, obligations, conformity-assessmen | alternatives |
| recommend_skills services.gera/mcp-gera-skills | unknown | Given a plain-language goal, return a ranked 'skill path' of the most relevant skills, scored by goal-term overlap. | alternatives |
| recognize_text chupre/yandex-vision-ocr-mcp | unknown | Synchronous OCR for images (JPEG/PNG/WEBP/HEIC/HEIF) and single-page PDFs. | alternatives |
| recognize_pdf chupre/yandex-vision-ocr-mcp | unknown | Asynchronous OCR for PDFs (single- or multi-page) and large files, via submit + poll. | alternatives |
| win_loss_analyzer io.github.shashwatgtm/revenue-enablement-mcp | unknown | Detect patterns in deal outcomes | alternatives |
| analyze_video ai-vision-mcp | unknown | Analyzes a video using AI (Google Gemini or Vertex AI) with a prompt and optional file source. | alternatives |
| analyze_image ai-vision-mcp | unknown | Analyzes an image using AI (Google Gemini or Vertex AI) with a prompt and optional file source. | alternatives |
| analyze_image_from_gcs ai-vision-mcp | unknown | Analyzes an image stored in Google Cloud Storage using AI. | alternatives |
| analyze_video_from_gcs ai-vision-mcp | unknown | Analyzes a video stored in Google Cloud Storage using AI. | alternatives |
| delegate_task @hugo.bastidas/minimax-plugin | unknown | Delegates a heavy token task to MiniMax M3 and returns a compact summary. | alternatives |
| extract TN0123/one-shot-ui | unknown | Analyze a screenshot into layout, color, and text data | alternatives |
| bober-run agent-bober | unknown | Run the full multi-agent pipeline (Researcher, Planner, Curator, Generator, Evaluator) for a feature or task. | alternatives |
| llms Siana2022/DinoRank MCP Proxy | unknown | LLM tool | alternatives |
| tfidf Siana2022/DinoRank MCP Proxy | unknown | TF-IDF analysis tool | alternatives |
| solvr_ta_analysis @ironbridgefoundation/ironbridge-mcp-server | unknown | Full technical analysis | alternatives |
| list_models ai.mafdet/mcp | unknown | List Mafdet AI models with provider, tier, and per-1M-token pricing | alternatives |
| simulate_run holycube/game-narrative-mcp | unknown | 对项目进行多次模拟运行 | alternatives |
| kuma_reflect plumpslabs/kuma | unknown | Reflection tool — checks if you're on track, detects drift (edits without tests, loops, unresolved failures), and suggests the next action. | alternatives |
| list_model_version_files picselliahq/picsellia-mcp | unknown | List files of a model version | alternatives |
| create_experiment picselliahq/picsellia-mcp | unknown | Create a new experiment | alternatives |
| launch_experiment picselliahq/picsellia-mcp | unknown | Launch an experiment | alternatives |
| attach_dataset_to_experiment picselliahq/picsellia-mcp | unknown | Attach a dataset to an experiment | alternatives |
| detach_dataset_from_experiment picselliahq/picsellia-mcp | unknown | Detach a dataset from an experiment | alternatives |
| set_experiment_base_model picselliahq/picsellia-mcp | unknown | Set the base model for an experiment | alternatives |
| list_deployments picselliahq/picsellia-mcp | unknown | List deployments in the organization | alternatives |
| get_deployment picselliahq/picsellia-mcp | unknown | Get details of a specific deployment | alternatives |
| get_deployment_monitoring_stats picselliahq/picsellia-mcp | unknown | Get monitoring statistics for a deployment | alternatives |
| list_deployment_predicted_assets picselliahq/picsellia-mcp | unknown | List predicted assets for a deployment | alternatives |
| list_experiment_logs picselliahq/picsellia-mcp | unknown | List logs for an experiment | alternatives |
| list_evaluation_artifacts picselliahq/picsellia-mcp | unknown | List artifacts of an evaluation | alternatives |
| list_model_versions picselliahq/picsellia-mcp | unknown | List versions of a model | alternatives |
| get_model_version picselliahq/picsellia-mcp | unknown | Get details of a model version | alternatives |
| get_experiment_log picselliahq/picsellia-mcp | unknown | Get a specific log from an experiment | alternatives |
| list_evaluations picselliahq/picsellia-mcp | unknown | List evaluations in the organization | alternatives |
| filter_experiment_logs picselliahq/picsellia-mcp | unknown | Filter logs of an experiment | alternatives |
| auditLLMCall @axonflow/sdk | unknown | Audits an LLM call by sending response summary, provider, model, token usage, and latency. | alternatives |
| configureMemoryTracker @lensmcp/memory-tracker | unknown | Set the active session id, event sink, context getter, and detector thresholds. | alternatives |
| onFlowSettled @lensmcp/memory-tracker | unknown | Compare each owner's attributed growth against leakItemThreshold; emit memory-retention for owners that grew and stayed resident. | alternatives |
| checkStaleGeneration @lensmcp/memory-tracker | unknown | On singleton disposal, emit singleton-stale-generation when retained bytes exceed staleGenerationBytesThreshold. | alternatives |
| predict_cochanges @metabob/mcp | unknown | GCN-based co-change prediction — no API call | alternatives |
| draft_reply io.github.RyanKramer/shippost-mcp | unknown | AI drafts a reply in your voice | alternatives |
| draft_tweet io.github.RyanKramer/shippost-mcp | unknown | AI drafts an original tweet | alternatives |
| draft_thread io.github.RyanKramer/shippost-mcp | unknown | AI drafts a full thread | alternatives |
| find_opportunities io.github.RyanKramer/shippost-mcp | unknown | AI scans your timeline for the best tweets to reply to | alternatives |
| analyze_account io.github.RyanKramer/shippost-mcp | unknown | AI analyzes any Twitter account | alternatives |
| get_performance io.github.RyanKramer/shippost-mcp | unknown | AI-powered engagement analytics | alternatives |
| score_job_fit rani700/CareerPilot | unknown | Ask the client's LLM to score how well a job matches your profile. | alternatives |
| agent_execute Crypto-Goatz/Rocket+ MCP Server | unknown | Run AI workflows (lead qual, proposals) | alternatives |
| skillforge_execute Crypto-Goatz/Rocket+ MCP Server | unknown | Execute AI skills | alternatives |
| insights_predict Crypto-Goatz/Rocket+ MCP Server | unknown | Predictive analytics | alternatives |
| spawn_agents @rk0429/agentic-relay | unknown | Spawns agent sessions, optionally linked to a task via agents[].task_id, with backend auto-selection from task_type. | alternatives |
| learning_report rio-swarm | unknown | Generates a learning report from the SONA Learning Engine. | alternatives |
| claude_code mcp-agents | unknown | Blocking tool to send a prompt to Claude Code and return the assistant result text. | alternatives |
| gemini mcp-agents | unknown | Send a prompt to the Antigravity CLI (agy) and return the result. | alternatives |
| sfs_extract_claims sfs-mcp-toolkit | unknown | Extract numerical claims from LLM output | alternatives |
| sfs_compute sfs-mcp-toolkit | unknown | End-to-end: extract claims, verify against evidence, and compute SFS score | alternatives |
| list_available_models io.github.AlephantAI/alephant-mcp | unknown | List available models | alternatives |
| list_agents io.github.AlephantAI/alephant-mcp | unknown | List agents in the workspace | alternatives |
| sara_insights io.github.Alessandro114/scala-score | unknown | AI-generated business insights | alternatives |
| sara_proactive io.github.Alessandro114/scala-score | unknown | Proactive AI suggestions | alternatives |
| list_models io.github.AlexFloyd13/clevername-mcp | unknown | Available AI models | alternatives |
| ask_llm io.github.AlexFloyd13/clevername-mcp | unknown | Call any provider by name | alternatives |
| ask_best io.github.AlexFloyd13/clevername-mcp | unknown | Route to the best model for the task | alternatives |
| ask_consensus io.github.AlexFloyd13/clevername-mcp | unknown | Ask multiple models and compare answers | alternatives |
| chat_complete io.github.AlexFloyd13/clevername-mcp | unknown | Chat with any model via your BYOK keys | alternatives |
| ask_claude io.github.AlexFloyd13/clevername-mcp | unknown | Call Anthropic with your key | alternatives |
| ask_gpt io.github.AlexFloyd13/clevername-mcp | unknown | Call OpenAI with your key | alternatives |
| ask_gemini io.github.AlexFloyd13/clevername-mcp | unknown | Call Google with your key | alternatives |
| estimate_risk_tool princeruhulofficial/Agent Accountability MCP Server | unknown | Estimate risk score for a planned tool call based on its past history. | alternatives |
| get_reliability_score_tool princeruhulofficial/Agent Accountability MCP Server | unknown | Get a 0-100 reliability score (like a report card) based on recent agent actions. | alternatives |
| suggest io.github.AlligatorC0der/conkurrence | unknown | AI-assisted schema improvement suggestions. | alternatives |
| run io.github.AlligatorC0der/conkurrence | unknown | Run convergence analysis on evaluation data. | alternatives |
| run_monte_carlo @retiregolden/mcp | unknown | Stochastic success rate and required-floor success rate | alternatives |
| batch_evaluate @retiregolden/mcp | unknown | Evaluate many policies against one household (search-friendly) | alternatives |
| run_optimizer @retiregolden/mcp | unknown | Engine optimizer / conversion schedule search | alternatives |
| solve_max_spending @retiregolden/mcp | unknown | Sustainable-spending bisection | alternatives |
| analyze_image RuyimgByCN/mcp-vision-server | unknown | Analyze an image using a vision model. Accepts URL, local file path, or Base64 string. | alternatives |
| analyze_image mcp-vision-bridge | unknown | Analyze one or more images via a multimodal model and return a detailed text description, OCR, UI spec, or answer to a specific question. | alternatives |
| openai_list_chat_models AceDataCloud/OpenAIMCP | unknown | List available chat/completion models | alternatives |
| openai_chat_completion AceDataCloud/OpenAIMCP | unknown | Create chat completions using OpenAI models | alternatives |
| openai_create_response AceDataCloud/OpenAIMCP | unknown | Create responses using the Responses API | alternatives |
| openai_create_embedding AceDataCloud/OpenAIMCP | unknown | Create text embedding vectors | alternatives |
| openai_list_image_models AceDataCloud/OpenAIMCP | unknown | List available image models | alternatives |
| openai_list_embedding_models AceDataCloud/OpenAIMCP | unknown | List available embedding models | alternatives |
| get_generation_status @anythingbutlabs/morphica-mcp | unknown | Poll a generation job | alternatives |
| list_models @anythingbutlabs/morphica-mcp | unknown | Available image models | alternatives |
| list_generations @anythingbutlabs/morphica-mcp | unknown | Recent generation history; takes limit (default 20) and cursor | alternatives |
| start_recommend_pipeline_run @reconcrap/boss-recommend-mcp | unknown | 异步启动推荐页筛选；先经过前置门禁，通过后返回ACCEPTED + run_id | alternatives |
| prepare_boss_chat_run @reconcrap/boss-recommend-mcp | unknown | 准备聊天页筛选运行 | alternatives |
| start_boss_chat_run @reconcrap/boss-recommend-mcp | unknown | 启动聊天页筛选运行 | alternatives |
| run_recommend @reconcrap/boss-recommend-mcp | unknown | start_recommend_pipeline_run的短别名；用户已经确认且要现在启动时优先调用 | alternatives |
| cancel_recommend_pipeline_run @reconcrap/boss-recommend-mcp | unknown | 取消运行中任务 | alternatives |
| pause_recommend_pipeline_run @reconcrap/boss-recommend-mcp | unknown | 请求暂停run；会在当前候选人处理完成后进入paused | alternatives |
| resume_recommend_pipeline_run @reconcrap/boss-recommend-mcp | unknown | 继续paused run；沿用同run_id与同CSV | alternatives |
| get_recommend_pipeline_run @reconcrap/boss-recommend-mcp | unknown | 用已知run_id轮询状态 | alternatives |
| list_recommend_pipeline_runs @reconcrap/boss-recommend-mcp | unknown | 只读列出最近run摘要并返回latest_run；忘记run_id时用它恢复 | alternatives |
| run_recruit_pipeline @reconcrap/boss-recommend-mcp | unknown | 启动搜索页筛选 | alternatives |
| start_recruit_pipeline_run @reconcrap/boss-recommend-mcp | unknown | 异步启动搜索页筛选 | alternatives |
| get_boss_chat_run @reconcrap/boss-recommend-mcp | unknown | 获取聊天页筛选运行状态 | alternatives |
| pause_boss_chat_run @reconcrap/boss-recommend-mcp | unknown | 暂停聊天页筛选运行 | alternatives |
| prepare_recommend_pipeline_run @reconcrap/boss-recommend-mcp | unknown | 只校验完整payload；不启动筛选。主要用于显式预检或定时任务前校验 | alternatives |
| get_recruit_pipeline_run @reconcrap/boss-recommend-mcp | unknown | 获取搜索页筛选运行状态 | alternatives |
| resume_recruit_pipeline_run @reconcrap/boss-recommend-mcp | unknown | 继续搜索页筛选运行 | alternatives |
| cancel_recruit_pipeline_run @reconcrap/boss-recommend-mcp | unknown | 取消搜索页筛选运行 | alternatives |
| list_providers io.github.HeshamFS/mcp-tool-factory | unknown | List available LLM providers | alternatives |
| forge_optimize io.github.RightNow-AI/forge-mcp-server | unknown | Submit PyTorch code for GPU kernel optimization using 32 parallel swarm agents. | alternatives |
| analyze_tweet itsbigdill/x-post-to-json MCP server | unknown | Fetch a tweet and return a fact-check scaffold with signals, claims, search queries, and rubric. | alternatives |
| transcribe_audio io.github.JXUE0/opencut-controller | unknown | Auto-transcribe audio from the timeline. | alternatives |
| pre_check_paper io.github.SelfPy/science-ai-mcp-server | unknown | Tier 1-5 acceptance probability from title + abstract (local FTS5, no LLM) | alternatives |
| ai_review_paper io.github.SelfPy/science-ai-mcp-server | unknown | Single-agent AI peer-review pass on a prepared prompt | alternatives |
| get_writer_pipeline_status io.github.SelfPy/science-ai-mcp-server | unknown | Get the status of the Article Writer pipeline | alternatives |
| predict_umbrella_needed saimoom026/weather-mcp-server | unknown | Prediction tool - applies threshold logic to forecast data to recommend whether you need an umbrella. | alternatives |
| get_travel_recommendation saimoom026/weather-mcp-server | unknown | Extended prediction tool - evaluates temperature, precipitation, wind, and conditions to rate travel suitability. | alternatives |
| forage io.github.Studio-Moser/shelbymcp | unknown | Run the scheduled enrichment skill: backfill embeddings, deduplicate, detect contradictions, generate digest | alternatives |
| polar4ai_create_models polardb-mysql-mcp-server | unknown | 使用polar4ai语法，创建各种自定义算法模型 | alternatives |
| qualify_prospect org.publicmcp/publicmcp | unknown | Fit score, vertical detection, service recommendation | alternatives |
| classify_intent AMEOBIUS-space/MCP Permission Guard | unknown | Classify a tool call into an intent category. | alternatives |
| risk_assess AMEOBIUS-space/MCP Permission Guard | unknown | Assess risk of a tool call on 0-100 scale. | alternatives |
| ideogram_describe takeshijuan/ideogram-mcp-server | unknown | Generate text descriptions from images. | alternatives |
| lbm_list_models io.github.SerpstatGlobal/llm-brand-monitor | unknown | List 350+ available LLM models | alternatives |
| lbm_get_usage io.github.SerpstatGlobal/llm-brand-monitor | unknown | Check credit balance and usage stats | alternatives |
| lbm_get_project io.github.SerpstatGlobal/llm-brand-monitor | unknown | Get project details with prompts and models | alternatives |
| lbm_create_project io.github.SerpstatGlobal/llm-brand-monitor | unknown | Create a new project | alternatives |
| lbm_update_project io.github.SerpstatGlobal/llm-brand-monitor | unknown | Update project name, models, or monitoring settings | alternatives |
| lbm_add_prompts io.github.SerpstatGlobal/llm-brand-monitor | unknown | Add monitoring prompts to a project | alternatives |
| lbm_delete_prompt io.github.SerpstatGlobal/llm-brand-monitor | unknown | Remove a prompt from a project | alternatives |
| lbm_run_scan io.github.SerpstatGlobal/llm-brand-monitor | unknown | Start a scan — sends prompts to LLMs and collects responses | alternatives |
| lbm_get_scan_status io.github.SerpstatGlobal/llm-brand-monitor | unknown | Check scan progress | alternatives |
| summarize_text infoshihab/MCP Pulse | unknown | Generates a short bullet summary of the provided text. | alternatives |
| summarize_pdf Naman-sys/StudyToolMCP | unknown | Extracts text from a PDF and returns a summary + 3-5 key points. | alternatives |
| solve_and_explain Naman-sys/StudyToolMCP | unknown | mode='math': symbolic solve via sympy, LLM fallback for word problems. mode='code': explains/debugs a code snippet via LLM. | alternatives |
| list_models io.github.codeChap/claude-chat | unknown | List available Claude models and their IDs (cached for 5 minutes). | alternatives |
| chat io.github.codeChap/claude-chat | unknown | Send a message to Claude. Supports multi-turn history, a system prompt, model selection, and extended thinking via thinking_budget. | alternatives |
| chat_with_vision io.github.codeChap/claude-chat | unknown | Analyse an image given an image URL and a text prompt. | alternatives |
| warm_up_translator huoshuiai42/huoshui-pdf-translator | unknown | Downloads required assets and models for faster subsequent translations. | alternatives |
| get_perspectives polydev-ai/polydev-ai | unknown | Query multiple AI models simultaneously | alternatives |
| enhance_prompt meigen | unknown | Turn short ideas into professional image prompts | alternatives |
| list_models meigen | unknown | List all available models for configured backends | alternatives |
| comfyui_workflow meigen | unknown | Manage ComfyUI workflow templates: list, view, import, modify, delete | alternatives |
| get_model_status audiogen-mcp | unknown | Check if model is loaded and device info | alternatives |
| predict_batch_failures io.github.NotHarshhaa/mainframe-mcp-server | unknown | Predictive risk scoring for recurring batch failures | alternatives |
| detectWorkflow @orchestrator-claude/mcp-server | unknown | Detect workflow type from prompt | alternatives |
| optimize_reasoning infranodus-mcp-server | unknown | Apply bias/coherence analysis to a reasoning trace or chat, steering toward optimal diversity and coherence. | alternatives |
| perf_verify io.github.Perf-AI/perf-mcp | unknown | Detect and repair hallucinations in LLM-generated text using multi-channel verification. | alternatives |
| perf_chat io.github.Perf-AI/perf-mcp | unknown | Route LLM requests to the optimal model automatically based on task complexity. | alternatives |
As of the latest check, Glimind tracks 200 ml AI agent (MCP) tools, of which 0 are healthy right now. The table below ranks them live-first by real-time reliability. Glimind rates each neutrally (0–100) from safe liveness probes plus privacy-clean real-usage outcomes — see each tool's live page for its current score and a working alternative if it's down.
Ranked live-first by current verdict (healthy → degraded → down), then by the neutral reliability score. Glimind sells no tools, so the ranking is unconflicted.
Every tool here links to its live alternatives — capability-matched substitutes that are healthy now. Or query https://glimind.com/v1/alternatives/{toolId}.
Live data via MCP/REST. Neutral ratings — Glimind only measures.